The Golden Formula To Get Positive Outcome From Visual Inspection Using AI

June 09, 2020

Noon - 1 PM ET


AI (Artificial Intelligence) and Deep Learning is one of the most lucrative skill sets both under COVID-19 and in a Post COVID-19 Era, where AI is needed to bring speed in a time of urgency, and contactless methods of operation in a time of social distance. NEC brings together our Visual Inspection Solution into the manufacturing world to create heightened product delivery through Quality excellence.  In order to harness this technology to expand visual inspections in manufacturing, you will need the golden formula containing: domain knowledge, big data, and deep learning of AI.

In this seminar we’ll explain how to eliminate your day to day quality inspection issues and leverage deep learning techniques to automate visual inspections by AI and detect hidden defects that are not detected by standard machine vision system.

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NEC Corporation of America

NEC has been providing solutions that help improve the way people live, work and communicate for over 117 years. NEC is a global leader in image recognition technologies backed with over half a century of accumulated knowledge and business performance. The latest deep learning based machine vision software, NEC RAPID Machine Learning, brings greater control and automation to manufacturing defect inspections for: automotive and a variety of industries. Utilizing its OneClass classification algorithm NEC RAPID Machine Learning can detect product defects simply by learning from only images of good product. Manufacturers do not need to collect defect images. NEC RAPID combined with the ability to be implemented into any existing machine vision system greatly reduces cost and training time. With 9 global research labs NEC places a heavy focus on innovation to continue to improve and deliver cutting edge solutions to our customers.

Image of Hans Peter Graf, Head of Department, NEC Laboratories America

Hans Peter Graf, Head of Department, NEC Laboratories America

Hans Peter Graf is head of the machine learning research department at NEC Laboratories America in Princeton. The department develops machine learning algorithms and systems, as well as a range of applications in semantic text analysis, cognitive video interpretation and bio-medical analytics. Several products have resulted from this technology, such as the e-Pathologist, a system assisting pathologists with the interpretation of histological samples. Another product is a system for visual inspection that is based on algorithms developed by the department. Hans Peter received a PhD in physics from the Swiss Federal Institute of Technology in Zurich, Switzerland. He is author or coauthor of over 100 reviewed articles and some 50 issued patents. He is a Fellow of the IEEE and a member of the American Physical Society.

Image of Himanshu Shekhar, Solutions Architect, NEC Corporation of America

Himanshu Shekhar, Solutions Architect, NEC Corporation of America

Himanshu Shekhar has around 20 years of experience in Analytics helping organization build cutting edge capability across various areas: predicting default, right asset allocation or redistribution of territory to optimize sales force. During his undergraduate and graduate studies, he applied AI to improve catalyst composition to improve CO-CO2 conversion and predict protein structure. He believes strongly in AI’s transformative power for business and is engaged in multiple initiative for NEC’s customers for better decisions, better products and optimized business processes. He holds a combined undergrad-grad degree from Indian Institute of Technology and Masters of Business Administration from Wharton Business School.

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